EFFECTS OF HETEROGENEOUS INFLUENCE OF INDIVIDUALS ON THE GLOBAL CONSENSUS

2010 ◽  
Vol 21 (08) ◽  
pp. 1011-1019 ◽  
Author(s):  
YING-TING LIN ◽  
HAN-XIN YANG ◽  
ZHI-HAI RONG ◽  
BING-HONG WANG
Keyword(s):  
Small World ◽  
Opinion Dynamics ◽  
Network Size ◽  
Power Exponent ◽  
Scale Free ◽  
Global Consensus ◽  
Optimal Value ◽  
Consensus Time ◽  
The Relationship

We propose an opinion dynamics model to study the effects of heterogeneous influence of individuals on the global consensus. Each individual is assigned a weight that is proportional to the power of its degree, where the power exponent α is an adjustable parameter. Interestingly, it is found that there exists an optimal value of α leading to the shortest consensus time for scale-free networks, random networks and small-world networks. Other quantities, such as the probability that an individual's initial opinion becomes the final opinion as a function of degree, the evolution of the number of opinion clusters, as well as the relationship between average consensus time and the network size, are also studied. Our results are helpful for understanding the role of heterogeneous influence in the opinion dynamics.

COMPLEX NETWORKS: TOPOLOGY, DYNAMICS AND SYNCHRONIZATION

2002 ◽  
Vol 12 (05) ◽  
pp. 885-916 ◽  
Author(s):  
XIAO FAN WANG
Keyword(s):  
Complex Networks ◽  
Network Models ◽  
Small World ◽  
Dynamical Networks ◽  
Scale Free ◽  
Epidemic Dynamics ◽  
The Past ◽  
The Relationship

Dramatic advances in the field of complex networks have been witnessed in the past few years. This paper reviews some important results in this direction of rapidly evolving research, with emphasis on the relationship between the dynamics and the topology of complex networks. Basic quantities and typical examples of various complex networks are described; and main network models are introduced, including regular, random, small-world and scale-free models. The robustness of connectivity and the epidemic dynamics in complex networks are also evaluated. To that end, synchronization in various dynamical networks are discussed according to their regular, small-world and scale-free connections.

EXPRESS PASSENGER TRANSPORT SYSTEM AS A SCALE-FREE NETWORK

2006 ◽  
Vol 20 (27) ◽  
pp. 1755-1761 ◽  
Author(s):  
BAIBAI FU ◽  
ZIYOU GAO ◽  
FASHENG LIU ◽  
XIANJUAN KONG
Keyword(s):  
Transport System ◽  
Network Topology ◽  
Small World ◽  
Power Exponent ◽  
Scale Free Network ◽  
Passenger Transport ◽  
Scale Free ◽  
Scale Free Networks ◽  
Highway Network ◽  
Free Network

An express highway itself is not a scale-free network, while the Express Passenger Transport System (EPTS) on the express highway network has the properties of a small-world and scale-free network. Data analysis based on the observation of the EPTS in Shandong province, China, shows that the EPTS has the properties of scale-free networks and the power exponent λ of the distribution is equal to about 2.1. Based on the scale-free network topology structure of the EPTS network, the construction of the EPTS network will be more efficient and robust.

scholarly journals Success in an Online Giving Day: The Role of Social Media in Fundraising

2019 ◽  
Vol 49 (1) ◽  
pp. 74-92 ◽  
Author(s):  
Abhishek Bhati ◽  
Diarmuid McDonnell
Keyword(s):  
Social Media ◽  
Organizational Factors ◽  
Network Size ◽  
Audience Engagement ◽  
Social Media Data ◽  
Size Number ◽  
Social Media Platforms ◽  
The Relationship ◽  
Media Data

Social media platforms offer nonprofits considerable potential for crafting, supporting, and executing successful fundraising campaigns. How impactful are attempts by these organizations to utilize social media to support fundraising activities associated with online Giving Days? We address this question by testing a number of hypotheses of the effectiveness of using Facebook for fundraising purposes by all 704 nonprofits participating in Omaha Gives 2015. Using linked administrative and social media data, we find that fundraising success—as measured by the number of donors and value of donations—is positively associated with a nonprofit’s Facebook network size (number of likes), activity (number of posts), and audience engagement (number of shares), as well as net effects of organizational factors including budget size, age, and program service area. These results provide important new empirical insights into the relationship between social media utilization and fundraising success of nonprofits.

scholarly journals Characterizing the Structure of the Railway Network in China: A Complex Weighted Network Approach

2019 ◽  
Vol 2019 ◽  
pp. 1-10 ◽  
Author(s):  
Weiwei Cao ◽  
Xiangnan Feng ◽  
Jianmin Jia ◽  
Hong Zhang
Keyword(s):  
Structural Characteristics ◽  
Flow Distribution ◽  
Small World ◽  
Centrality Measures ◽  
Railway Network ◽  
Weighted Network ◽  
Scale Free ◽  
Topological Measures ◽  
Free Network

Understanding the structure of the Chinese railway network (CRN) is crucial for maintaining its efficiency and planning its future development. To advance our knowledge of CRN, we modeled CRN as a complex weighted network and explored the structural characteristics of the network via statistical evaluations and spatial analysis. Our results show CRN as a small-world network whose train flow obeys power-law decaying, demonstrating that CRN is a mature transportation infrastructure with a scale-free structure. CRN also shows significant spatial heterogeneity and hierarchy in its regionally uneven train flow distribution. We then examined the nodal centralities of CRN using four topological measures: degree, strength, betweenness, and closeness. Nodal degree is positively correlated with strength, betweenness, and closeness. Unlike the common feature of a scale-free network, the most connected nodes in CRN are not necessarily the most central due to underlying geographical, political, and socioeconomic factors. We proposed an integrated measure based on the four centrality measures to identify the global role of each node and the multilayer structure of CRN and confirm that stable connections hold between different layers of CRN.

THE GENERAL OWNERSHIP STRUCTURE OF THE EUROPEAN AEROSPACE INDUSTRY A STATISTICAL AND NETWORK ANALYSIS

2021 ◽  
Vol 24 (05) ◽  
Author(s):  
LUCIO BIGGIERO ◽  
ROBERT MAGNUSZEWSKI
Keyword(s):  
Ownership Structure ◽  
Business Groups ◽  
Small World ◽  
Equity Capital ◽  
Scale Free ◽  
Topological Parameters ◽  
New Methods ◽  
Aerospace Companies ◽  
Capital Transfer

In this paper, we investigate the ownership structure of the 3143 EU28 aerospace companies in 2019, and extend the analysis to the 2428 neighbor partners outside EU28 and/or aerospace. Different from the previous studies, we consider all equity capital flows regardless of their size, and their monetary value instead of the corresponding ownership share. We further innovate by applying new methods to measure degree of influence power and hierarchical structure. The resulting picture shows that between the pure EU28 aerospace companies: (i) ownership relationships concern only relatively few companies (10%), which trigger horizontal and vertical structures; (ii) density is extremely low; (iii) relationships are fully hierarchical with no cross-ownership; (iv) capital is seldom transferred across business groups; (v) most of the main topological parameters have a typically polarized scale-free structure. When including also the ownership neighbors, some of those traits change substantially: (i) the share of connected companies substantially grows up to 63%; (ii) size and length of the largest pyramidal structures will grow remarkably, reaching a top of 874 companies; (iii) the industry becomes a full small-world structure, thus allowing huge capital transfer across business groups. Finally, a dramatic financialization, meant as a pivotal and quantitatively heavy role of financial operators, emerges also as a clear characteristic of the extended network.

scholarly journals The Linkage between Sustainability and Innovation Performance in IT Hardware Sector

2019 ◽  
Vol 11 (16) ◽  
pp. 4275 ◽  
Author(s):  
Francesca Michelino ◽  
Antonello Cammarano ◽  
Andrea Celone ◽  
Mauro Caputo
Keyword(s):  
Corporate Sustainability ◽  
Innovation Performance ◽  
Patent Data ◽  
Optimal Value ◽  
Definition Of ◽  
The Relationship ◽  
Sustainability Framework ◽  
Innovation Processes ◽  
Hardware Industry

This work investigates the relationship between sustainability and innovation performance. Despite the relevance of the issue, few contributions deepen such a relationship after both a conceptual and a quantitative perspective. Therefore, the aim of this paper is to suggest a measure of sustainability for innovation processes and to define which innovation strategies can lead to more sustainable processes. The role of ambidexterity within the corporate sustainability framework is underlined: Ambidextrous organizations are able to improve the innovation performance and better use their resources, improving the sustainability of research and development (R&D) processes. By employing patent data and testing the framework on a sample of worldwide top R&D spending companies in the IT hardware industry, this work suggests which optimal value of ambidexterity will lead to more sustainable innovation. In addition, R&D processes with non-optimal levels of ambidexterity can be managed in a better way. Indeed, results show the usefulness of open innovation adoption to improve the performance of exploration processes. Moreover, R&D activities based on a preponderance of exploitation strategies are more sustainable if they fall into technological domains in which the focal company is highly specialized. The work also contributes to the conceptualization of sustainability and to definition of patent-based metrics related to sustainability.

CONSENSUS FORMATION IN WEIGHTED SCALE-FREE NETWORKS

2009 ◽  
Vol 20 (05) ◽  
pp. 677-686 ◽  
Author(s):  
KE HU ◽  
YI TANG
Keyword(s):  
Opinion Dynamics ◽  
Opinion Formation ◽  
Consensus Formation ◽  
Scale Free ◽  
Weighted Networks ◽  
Global Consensus ◽  
Dynamical Behaviors ◽  
Scale Free Networks ◽  
Unweighted Network ◽  
Large Heterogeneity

We develop a consensus model for studying opinion dynamics in weighted networks and investigate the effects of both the distribution of weights and the correlations between weight and degree on dynamical behaviors of opinion formation. Our results suggest that a global consensus in the weighted networks to reach is more difficult than that in unweighted network, and strongly depends on the heterogeneity of connection strengths. In addition, in the weighted network with very large heterogeneity of connection strengths, only single macroscopic opinion cluster can be formed, which differs from the behavior in the unweighted network where the next-largest macroscopic opinion cluster may exist.

scholarly journals Developing Knowledge-Based Resources: The Role of Entrepreneurs’ Social Network Size and Trust

2018 ◽  
Vol 10 (10) ◽  
pp. 3380 ◽  
Author(s):  
Miaomiao Yin ◽  
Asghar Jahanshahi
Keyword(s):  
Social Networks ◽  
Social Network ◽  
New Ventures ◽  
Business Environment ◽  
Network Size ◽  
Knowledge Based ◽  
Social Network Size ◽  
The Relationship ◽  
Developing Knowledge

Entrepreneurs’ social networks play a crucial role in developing knowledge-based resources for their new ventures. Although most studies in an entrepreneurship context find that trust is very important when entrepreneurs develop social networks, limited research examines how trust can explain the variation in the relationship between an entrepreneur’s social networks and a firm’s knowledge-based resources. Therefore, the major objective of the paper is to understand the effects of the size of an entrepreneur’s social network on his or her firm’s knowledge-based resources with high and low levels of trust. Our data were collected from surveys administered to 476 entrepreneurs in China in 2018. Our multiple regression analysis indicates that social networks reinforce knowledge-based resources in a situation where entrepreneurs highly trust their major networks partners in their business environment (e.g., family, close friends, consultants, suppliers, peers, etc.). However, with a low level of trust, the relationship between social network and knowledge-based resources is curvilinear (inverse U-shaped). Our empirical validations showed that the relationship between social network and a firm’s knowledge-based resources is highly contingent to the level of trust among network members.

Opinion dynamics in typical networks with local and global social impacts together

2020 ◽  
Vol 31 (08) ◽  
pp. 2050110
Author(s):  
Liangfang Wu ◽  
Shiyang Liu ◽  
Huimin Zhang
Keyword(s):  
Initial Density ◽  
Heat Bath ◽  
Small World ◽  
Opinion Dynamics ◽  
Social Impacts ◽  
Scale Free Network ◽  
Scale Free ◽  
Free Network ◽  
Opinion Model ◽  
Main Determinants

We introduce a new opinion model to study the opinion evolving in three typical networks (small-world network, scale-free network and highly clustered scale-free network) by employing Monte Carlo numerical simulation. To consider important social influence, we propose a heat bath like optimized opinion model that includes both local and global social impacts. By employing the new opinion model into three typical networks, we have found the main determinants of the evolution of the opinion, that were the weight constant of the local and global effects, the structure of the network, the size of the network and the initial density of the average opinion. The simulations show how those factors affect the evolving time of reaching the consensus quantitatively. Our model also could explain the cases of de facto standard and lock-in effect, well-known phenomenon in economics and business management.

scholarly journals Quantitative Controllability Index of Complex Networks

2018 ◽  
Vol 2018 ◽  
pp. 1-9
Author(s):  
Lifu Wang ◽  
Yali Zhang ◽  
Jingxiao Han ◽  
Zhi Kong
Keyword(s):  
Complex Networks ◽  
Condition Number ◽  
Random Network ◽  
Small World ◽  
Scale Free Network ◽  
Scale Free ◽  
Network Topologies ◽  
Free Network ◽  
The Relationship ◽  
Controllability Index

In this paper, the controllability issue of complex network is discussed. A new quantitative index using knowledge of control centrality and condition number is constructed to measure the controllability of given networks. For complex networks with different controllable subspace dimensions, their controllability is mainly determined by the control centrality factor. For the complex networks that have the equal controllable subspace dimension, their different controllability is mostly determined by the condition number of subnetworks’ controllability matrix. Then the effect of this index is analyzed based on simulations on various types of network topologies, such as ER random network, WS small-world network, and BA scale-free network. The results show that the presented index could reflect the holistic controllability of complex networks. Such an endeavour could help us better understand the relationship between controllability and network topology.

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